ArticleJournal of biomedical informatics2024
MultiWD: Multi-label wellness dimensions in social media posts.
Article in Journal of biomedical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- The Rise of Small Language Models in Healthcare: A Comprehensive Survey.Computer science review · 2026Article
- Early detection of mental health on social media using a hybrid Bi-LSTM-XGBoost model: a comparative study.Scientific reports · 2026Article
- Multi-label mental health classification in social media posts with multi-perspective prompt ensemble and auxiliary self-supervision.Scientific reports · 2025Article
- Comparative performance of large language models in emotional safety classification across sizes and tasks.Frontiers in artificial intelligence · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
Abstract
backgroundHalbert L. Dunn's concept of wellness is a multi-dimensional aspect encompassing social and mental well-being. Neglecting these dimensions over time can have a negative impact on an individual's mental health. The manual efforts employed in in-person therapy sessions reveal that underlying factors of mental disturbance if triggered, may lead to severe mental health disorders.
objectiveIn our research, we introduce a fine-grained approach focused on identifying indicators of wellness dimensions and mark their presence in self-narrated human-writings on Reddit social media platform. DESIGN AND
methodWe present the MultiWD dataset, a curated collection comprising 3281 instances, as a specifically designed and annotated dataset that facilitates the identification of multiple wellness dimensions in Reddit posts. In our study, we introduce the task of identifying wellness dimensions and utilize state-of-the-art classifiers to solve this multi-label classification task.
resultsOur findings highlights the best and comparative performance of fine-tuned large language models with fine-tuned BERT model. As such, we set BERT as a baseline model to tag wellness dimensions in a user-penned text with F1 score of 76.69.
conclusionOur findings underscore the need of trustworthy and domain-specific knowledge infusion to develop more comprehensive and contextually-aware AI models for tagging and extracting wellness dimensions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.